Implantable medical device and method for detecting cardiac events without using of refractory or blanking periods

ABSTRACT

Cardiac electrical events are detected by comparing signal vectors with pre-determined classification zones representative of different cardiac events. The signal vector is generated by sensing the voltages between various combinations of electrodes, such as A-tip to V-tip, A-tip to A-ring, and A-ring to V-ring. The signal vector is compared with a set of classification zones corresponding to different events, such as P-waves, R-waves, T-waves, A-pulses, and V-pulses, to determine whether the vector lies within any of the classification zones. In this manner, cardiac events are detected using only the voltages received from the electrodes and no refractory periods or blanking periods are required to distinguish one event from another. The classification zones vary from patient to patient and a technique is provided herein for generating a set of vector classification zones for a particular patient. Signal vectors corresponding to various unknown cardiac events are generated by the implanted device and are transmitted to an external device programmer. ECG signals, generated by a surface ECG detector, are simultaneously received by the external programmer. The external programmer identifies the cardiac electrical event corresponding to each signal vector based on the ECG signals and then generates classification zones for each event type using only the signal vectors corresponding to the event.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to copending U.S. patent application Ser.No. 10/193,040, filed Jul. 10, 2002, titled “IMPLANTABLE MEDICAL DEVICEAND METHOD FOR DETECTING CARDIAC EVENTS WITHOUT USING OF REFRACTORY ORBLANKING PERIODS.”

FIELD OF THE INVENTION

The invention generally relates to implantable medical devices, such aspacemakers or implantable cardioverter-defibrillators (“ICDs”) and, inparticular, to techniques for detecting electrical cardiac events usingan implantable medical device.

BACKGROUND OF THE INVENTION

A pacemaker is a medical device, typically implanted within a patient,which recognizes various disrythmias such as an abnormally slow heartrate (bradycardia) or an abnormally fast heart rate (tachycardia) anddelivers electrical pacing pulses to the heart in an effort to remedythe disrythmias. An ICD is a device, also implantable into a patient,which additionally recognizes atrial fibrillation (AF) or ventricularfibrillation (VF) and delivers electrical shocks to terminatefibrillation.

Pacemakers and ICDs carefully monitor characteristics of the heart suchas the heart rate to detect disrythmias, discriminate among differenttypes of disrythmias, identify appropriate therapy, and determine whento administer the therapy. The heart rate, for example, is monitored byexamining the electrical signals that are manifest concurrent with thedepolarization or contraction of the myocardial tissue of the heart. Theelectrical signals are detected internally by sensing leads mountedwithin the heart and are referred to as intracardiac electrogram(“IEGM”) signals. The normal contraction of atrial muscle tissue appearsas a P-wave within the IEGM. A sequence of consecutive P-waves definesthe atrial rate. The normal contraction of ventricular muscle tissueappears as an R-wave (sometimes referred to as the “QRS complex”) withinthe IEGM. A sequence of consecutive R-waves defines the ventricularrate. If the heart is subject to flutter or fibrillation, P-waves andR-waves typically cannot be discerned within the IEGM. Hence, thepacemaker or ICD may need to rely on other characteristics of the IEGMto discriminate among different types of flutter and fibrillation, toidentify optimal therapy, and to determine when to administer thetherapy. Some state of the art pacemakers and ICDs are capable ofsensing electrical signals independently in the atria and in theventricles. Hence, an atrial IEGM and a separate ventricular IEGM aredetected. The atrial rate is determined based upon P-waves detected inthe atrial IEGM. The ventricular rate is determined based upon R-wavesdetected within the ventricular IEGM.

Thus pacemakers and ICDs administer therapy to the heart, in part, basedupon the detection of electrical characteristics of the heart such asP-waves, R-waves, atrial rate, ventricular rate, and the like. As onespecific example, if the atrial and ventricular rates are both below aminimum acceptable heart rate threshold or if long gaps appear withinthe IEGM signals wherein no P-waves and R-waves are sensed, the cardiacpacing device thereby concludes that the patient is suffering frombradycardia and administers pacing pulses in an effort to increase theheart rate or to eliminate long gaps without heart beats. As anotherspecific example, if the atrial and ventricular rates are well above amaximum expected heart rate, the cardiac pacing device concludes thatthe patient is suffering from a tachyarrhythmia and administersappropriate therapy such as, for example, overdrive pacing in an effortto lower the heart rate to within an acceptable range. If the atrialrate is found to be extremely high, but the ventricular rate isrelatively normal, the cardiac pacing device concludes that the patientis suffering from atrial flutter or atrial fibrillation and administersa defibrillation pulse to the atria. If the ventricular rate isextremely fast and chaotic, the cardiac pacing device concludes that thepatient is suffering from ventricular fibrillation and administers adefibrillation pulse directly to the ventricles. Details regardingtechniques for discriminating between atrial and ventricular disrythmiasor arrhythmias are provided in U.S. Pat. No. 5,620,471 to Duncanentitled “System and Method for Discriminating Between Atrial andVentricular Arrhythmias and for Applying Cardiac Therapy Therefor”,issued Apr. 15, 1997, which is incorporated by reference herein.

Reliable operation of pacemakers and ICDs therefore necessitates thatthe device be capable of accurately detecting P-waves, R-waves or otherelectrical events originating within the heart. Insofar as P-waves areconcerned, however, the afore-mentioned R-waves, though initiallygenerated within the ventricles, propagate into the atria and may bedetected therein as part of the atrial IEGM signal. It is thereforepossible for the device, upon detecting an electrical pulse within theatria, to misidentify a far field R-wave as being a P-wave. As a result,any functions performed by the pacemaker, which require accuratedetection of P-waves, may not function as intended. For example, thecalculated atrial rate will be higher than the actual atrial rate,perhaps causing the device to erroneously conclude that the atria aresubject to a tachyarrhythmia, which does not in fact exist.Alternatively, the overestimated atrial heart rate may cause the deviceto fail to detect a bradycardia, which does exist. As a result,inappropriate therapy may be administered. For an ICD, an erroneouslyhigh determination of the atrial rate may cause the ICD to incorrectlyconclude that the heart is subject to atrial fibrillation, resulting ina potentially painful cardioversion pulse administered to the atrium.

Thus, it is necessary to properly distinguish P-waves or otherelectrical events originating in the atria from far field R-waves orother events originating in the ventricles. Accordingly, moststate-of-the-art pacemakers ignore any events detected within the atriaduring a predetermined period of time subsequent to the detection of anR-wave in the ventricles. This period of time is referred to as thepost-ventricular atrial blanking (PVAB) interval or a post-ventricularatrial refractory period (PVARP). Briefly, upon the detection of anR-wave from a sensing electrode positioned within the ventricles, thepacemaker thereafter ignores any events detected from a sensing leadwithin the atria for a period of time (e.g. 225 ms.) under theassumption that any event detected during that period of time isactually a far field R-wave.

The need to use numerous relative and absolute blanking and refractoryperiods has various disadvantages. The blanking and refractory periodsmust be carefully set for the device to function properly. This requiresa careful and time-consuming review by the physician of programmingparameters used to set the refractory and blanking periods within theimplanted device and may necessitate several follow-up sessions betweenpatient and physician before the parameters are set properly. Also, thediscrimination algorithm employed by the implanted device is quitecomplicated and prone to event misidentification.

One example of a problem that can arise when using refractory andblanking periods involves the misidentification of far field R-waves asP-waves. In this regard, the use of a PVAB interval presupposes that theR-wave will be detected in the ventricles before it appears as afar-field R-wave in the atria. This is not always the case. However,circumstances can arise wherein a far field R-wave is detected withinthe atria before it is detected within the ventricles. This may occur,for example, if an atrial sensing lead is positioned closer to thesource of an R-wave than the ventricular sensing leads. Anothercircumstance wherein an R-wave may be detected within the atria withouta preceding R-wave detection in the ventricles occurs if the thresholdfor R-wave detection in the ventricles is set too high, such that someR-waves are not detected at all within the ventricles. In any event, ifthe far field R-wave is detected within the atria without an immediatelypreceding R-wave detection in the ventricles, the aforementioned PVABinterval is ineffective to filter out the far field R-wave from theatrial IEGM. As a result, far field R-waves are misclassified as P-wavesresulting in incorrect determination of atrial rate, or other criticalparameters, causing potentially erroneous therapy to be administered bythe pacemaker.

Another example of a problem that can arise when using refractory andblanking periods involves the miscalculation of high atrial rates whenusing Combipolar sensing. (“Combipolar” is a trademark of St. JudeMedical.) With Combipolar sensing, a pair of unipolar leads ispositioned within the heart, one in the atrium and one in the ventricle.A ventricular channel IEGM signal is generated in the same manner aswith unipolar sensing wherein electrical voltage differentials aredetected between the tip of the ventricular lead and the body of thedevice. However, the atrial channel of the IEGM signal is generated bydetecting voltage differentials between the electrodes at the tips ofthe atrial and ventricular leads. A logic system internal to thepacemaker determines whether the signal is an atrial signal or aventricular signal. More specifically, a signal detected on both theatrial and ventricular channels is regarded as a ventricular signal. Asignal detected only on the atrial channel is regarded as a true atrialsignal. A signal detected only on the ventricular channel is regarded asbeing of extracardiac origin. For a more complete description ofCombipolar systems, see U.S. Pat. No. 5,522,855 (Hoegnelid),incorporated herein by reference.

However, when using Combipolar sensing, intrinsic ventricular signalsare always recorded on the atrial channel. This is not a problem whenthe intrinsic ventricular signal is also detected on the ventricularchannel since the logic of the Combipolar system will regard the signalas being a ventricular signal, but if an intrinsic signal arising in theventricle is not detected on the ventricular channel but only on theatrial channel, it will be treated as a P-wave. Such may be the casewith the T-wave, which typically coincides with the VentricularRefractory Period (VRP)—a period of time when the ventricular channel isnot capable of responding to intrinsic signals. Accordingly, the use ofconventional blanking and refractory periods in connection withCombipolar sensing can result in T-waves being misidentified as P-waves,thereby yielding an incorrect atrial rate, particularly at high atrialrates.

Accordingly, it would be desirable to provide an improved technique fordetecting electrical events originating within the heart, which does notrequire use of blanking and refractory periods, and it is to that endthat aspects of the present invention are primarily directed.

SUMMARY OF THE INVENTION

In accordance with one aspect of the invention, a technique is providedfor detecting electrical events in the heart of the patient withoutusing blanking or refractory periods. Rather, electrical events aredetected by comparing signal vectors generated from combinations ofelectrodes with pre-determined classification zones. The technique isperformed by an implantable cardiac stimulation device for implantwithin a patient wherein the device has multiple electrodes. Electricalsignals are sensed by selected combinations of the electrodes and asignal vector is generated that is representative of the electricalsignals. Then, the signal vector is compared with a set of predeterminedvector classification zones, each representative of a range of signalvectors for different cardiac electrical events, to classify theelectrical event. By directly comparing signal vectors with eventclassification zones, blanking and refractory periods are not required.

In one example, a signal vector is generated by sensing the voltagesbetween various combinations of electrodes, such as sensing an A-tip toV-tip voltage, an A-tip to A-ring voltage, an A-ring to V-ring voltage,an A-ring to V-ring voltage, and a V-ring to coil voltage. The signalvector specifies the amplitudes of the voltage signals derived fromthose electrode combinations. The signal vector is compared with a setof classification zones, each corresponding to a different event, suchas a P-wave, R-wave, T-wave, A-pulse, V-pulse, PAC, or PVC, to determinewhether the vector lies within any of the classification zones. Theclassification zones are each specified by a unique geometrical range,defined by a direction vector, a maximum angle from the vector, aminimum vector length and a maximum vector length. For P-waves, forexample, there is a corresponding P-wave zone specifying a P-wavedirection vector, a maximum angle from the P-wave direction vector, aminimum P-wave vector length and a maximum P-wave vector length. If thesignal vector lies within the geometric range for the P-waveclassification zone, the signal vector is thereby identified as being aP-wave. If not, the signal vector is compared with other classificationzones. If the signal vector does not lie within the within the geometricrange of any for the classification zones, then it is designated as anunclassified event, typically electrical noise.

In another example, rather than comparing individual signal vectors toindividual classification zones, a sequence of signal vectors iscompared with a sequence of vector classification zones. For example, ifa pair of consecutive signal vectors matches a classification zonesequence representing a P-wave followed by a QRS-complex, the pair ofevents may thereby be identified as being a normal sinus beat. Atrialfibrillation, ventricular fibrillation or other such events may also bedetected using these techniques.

In accordance with another aspect of the invention, a technique isprovided for determining a set of vector classification zones for aparticular patient. The technique may be performed, for example, by adevice programmer in communication with an implanted cardiac stimulatingdevice and a surface ECG detector. Signal vectors, generated by theimplanted device, are input by the device programmer for various cardiacelectrical events in the heart of the patient. ECG signals, generated bya surface ECG detector attached to the patient, are also input by thedevice programmer. The ECG signals represent the same cardiac electricalevents as the signal vectors. The device programmer identifies theelectrical events based on ECG signals and then labels the varioussignal vectors accordingly. Then, for a given event type, the deviceprogrammer generates the event classification zone for that event typebased on all of the signal vectors that had been correlated with theevent type, i.e. all signal vectors labeled as corresponding to theevent type based on the ECG analysis.

For example, the device programmer takes all signal vectors identifiedas being P-waves, based on the ECG, and determines the geometric rangefor the P-wave classification zone based on the P-wave signal vectors.In this regard, the device programmer determines the P-wave directionvector, the maximum angle relative to the P-wave direction vector, theminimum P-wave vector length and the maximum P-wave vector length. TheP-wave direction vector is determined by averaging the directions of allof the individual P-wave vectors. The maximum angle relative to theP-wave direction vector is determined by finding the individual P-wavehaving the greatest angular deviation from the P-wave direction vector.The maximum P-wave vector length is determined by finding the individualP-wave having the greatest vector length. The minimum P-wave vectorlength is determined by finding the individual P-wave having theshortest vector length. Preferably a large number of individual cardiacevents are detected under different patient conditions before thegeometric ranges of the various event types are generated. Also, theresulting geometric ranges are each preferably enlarged by adding safetymargins to the minimum vector length, maximum vector length, and maximumangle relative to the direction vector.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features and advantages of the present invention may be morereadily understood by reference to the following description taken inconjunction with the accompanying drawings, in which:

FIG. 1 is a simplified diagram illustrating an implantable stimulationdevice in electrical communication with at least three leads implantedinto a patient's heart for delivering multi-chamber stimulation andshock therapy;

FIG. 2 is a functional block diagram of the multi-chamber implantablestimulation device of FIG. 1 illustrating the basic elements of astimulation device which can provide cardioversion, defibrillation andpacing stimulation in four chambers of the heart and particularlyillustrating a vector-based cardiac event detection unit for classifyingelectrical events sensed in the heart;

FIG. 3 is a functional block diagram illustrating components of aprogrammer for use in programming the implantable device of FIG. 1, andin particular illustrating a vector-based event detection set-up unitfor use in programming the event detection unit of the implantabledevice;

FIG. 4 is a logic circuit diagram illustrating an exemplary portion ofthe sensing circuitry of the device of FIG. 2, which provide signals tothe vector-based event detection unit;

FIG. 5 is a graphic representation of a first exemplary set of signalvector clusters processed by the vector-based event detection unit ofFIG. 2;

FIG. 6 is a graphic representation of a second exemplary set of signalvector clusters also processed by the vector-based event detection unitof FIG. 2;

FIG. 7 is a graphic representation of an exemplary set of classificationzones used by the vector-based event detection unit of FIG. 2 toidentify signal vectors such as those of FIGS. 5 and 6;

FIG. 8 is a graphic representation of single exemplary classificationzone used by the vector-based event detection unit of FIG. 2,particularly illustrating geometric parameters associated therewith;

FIG. 9 illustrates a first exemplary technique performed by thevector-based cardiac event detection unit of FIG. 2 for classifyingindividual electrical events sensed in the heart using signal vectorsand pre-determined classification zones;

FIG. 10 illustrates an exemplary technique performed by the set-up unitof the programmer of FIG. 3 for generating the set of classificationzones;

FIG. 11 illustrates an exemplary technique performed by the set-up unitof the programmer of FIG. 3 for determining geometric ranges for theclassification zones of FIG. 10;

FIG. 12 illustrates a second exemplary technique performed by thevector-based cardiac event detection unit of FIG. 2 for classifying asequence of electrical events sensed in the heart using sequences ofsignal vectors and pre-determined classification zones.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description includes the best mode presently contemplatedfor practicing the invention. The description is not to be taken in alimiting sense but is made merely for the purpose of describing thegeneral principles of the invention. The scope of the invention shouldbe ascertained with reference to the issued claims. In the descriptionof the invention that follows, like numerals or reference designatorswill be used to refer to like parts or elements throughout.

Exemplary systems and methods using signal vectors are described forclassifying electrical events, such P-waves, R-waves, etc., sensedwithin the heart of a patient. The classification method is performed byan implantable cardiac stimulation service subject to programmingcommands received from an external programmer. Initially, an overview ofthe implanted device is provided with reference to FIGS. 1 and 2 and anoverview of an external programmer used to program the device is thenprovided with reference to FIG. 3. An overview of the mathematicsunderlying the vector-based technique is then provided with reference toFIGS. 4–8. An exemplary technique for classifying individual electricalevents using the vector-based technique is provided with reference tothe flowcharts of FIG. 9. The vector-based technique employsclassification zones, which are unique to each patient. An exemplarytechnique for generating the classification zones is provided withreference to the flowcharts of FIGS. 10–11. Then, an exemplary techniquefor classifying sequences of electrical events is provided withreference to the flowchart of FIG. 12. In the flow charts, the variousalgorithmic steps are summarized in individual “blocks”. Such blocksdescribe specific actions or decisions that must be made or carried outas the algorithm proceeds. Where a microcontroller (or equivalent) isemployed, the flow charts presented herein provide the basis for a“control program” that may be used by such a microcontroller (orequivalent) to effectuate the desired control of the stimulation deviceor external programmer. Those skilled in the art may readily write sucha control program based on the flow charts and other descriptionspresented herein.

Implantable Device Overview

As shown in FIG. 1, there is a stimulation device 10 in electricalcommunication with a patient's heart 12 by way of three leads, 20, 24and 30, suitable for delivering multi-chamber stimulation and shocktherapy. To sense atrial cardiac signals and to provide right atrialchamber stimulation therapy, the stimulation device 10 is coupled to animplantable right atrial lead 20 having at least an atrial tip electrode22, which typically is implanted in the patient's right atrialappendage.

To sense left atrial and ventricular cardiac signals and to provide leftchamber pacing therapy, the stimulation device 10 is coupled to a“coronary sinus” lead 24 designed for placement in the “coronary sinusregion” via the coronary sinus os for positioning a distal electrodeadjacent to the left ventricle and/or additional electrode(s) adjacentto the left atrium. As used herein, the phrase “coronary sinus region”refers to the vasculature of the left ventricle, including any portionof the coronary sinus, great cardiac vein, left marginal vein, leftposterior ventricular vein, middle cardiac vein, and/or small cardiacvein or any other cardiac vein accessible by the coronary sinus.

Accordingly, an exemplary coronary sinus lead 24 is designed to receiveatrial and ventricular cardiac signals and to deliver left ventricularpacing therapy using at least a left ventricular tip electrode 26, leftatrial pacing therapy using at least a left atrial ring electrode 27,and shocking therapy using at least a left atrial coil electrode 28.

The stimulation device 10 is also shown in electrical communication withthe patient's heart 12 by way of an implantable right ventricular lead30 having, in this embodiment, a right ventricular tip electrode 32, aright ventricular ring electrode 34, a right ventricular (RV) coilelectrode 36, and an SVC coil electrode 38. Typically, the rightventricular lead 30 is transvenously inserted into the heart 12 so as toplace the right ventricular tip electrode 32 in the right ventricularapex so that the RV coil electrode will be positioned in the rightventricle and the SVC coil electrode 38 will be positioned in thesuperior vena cava. Accordingly, the right ventricular lead 30 iscapable of receiving cardiac signals, and delivering stimulation in theform of pacing and shock therapy to the right ventricle.

As illustrated in FIG. 2, a simplified block diagram is shown of themulti-chamber implantable stimulation device 10, which is capable oftreating both fast and slow arrhythmias with stimulation therapy,including cardioversion, defibrillation, and pacing stimulation. While aparticular multi-chamber device is shown, this is for illustrationpurposes only, and one of skill in the art could readily duplicate,eliminate or disable the appropriate circuitry in any desiredcombination to provide a device capable of treating the appropriatechamber(s) with cardioversion, defibrillation and pacing stimulation.

The housing 40 for the stimulation device 10, shown schematically inFIG. 2, is often referred to as the “can”, “case” or “case electrode”and may be programmably selected to act as the return electrode for all“unipolar” modes. The housing 40 may further be used as a returnelectrode alone or in combination with one or more of the coilelectrodes, 28, 36 and 38, for shocking purposes. The housing 40 furtherincludes a connector (not shown) having a plurality of terminals, 42,44, 46, 48, 52, 54, 56, and 58 (shown schematically and, forconvenience, the names of the electrodes to which they are connected areshown next to the terminals). As such, to achieve right atrial sensingand pacing, the connector includes at least a right atrial tip terminal(AR TIP) 42 adapted for connection to the atrial tip electrode 22.

To achieve left chamber sensing, pacing and shocking, the connectorincludes at least a left ventricular tip terminal (V_(L) TIP) 44, a leftatrial ring terminal (A_(L) RING) 46, and a left atrial shockingterminal (A_(L) COIL) 48, which are adapted for connection to the leftventricular ring electrode 26, the left atrial tip electrode 27, and theleft atrial coil electrode 28, respectively.

To support right chamber sensing, pacing and shocking, the connectorfurther includes a right ventricular tip terminal (V_(R) TIP) 52, aright ventricular ring terminal (V_(R) RING) 54, a right ventricularshocking terminal (R_(V) COIL) 56, and an SVC shocking terminal (SVCCOIL) 58, which are adapted for connection to the right ventricular tipelectrode 32, right ventricular ring electrode 34, the RV coil electrode36, and the SVC coil electrode 38, respectively.

At the core of the stimulation device 10 is a programmablemicrocontroller 60, which controls the various modes of stimulationtherapy. As is well known in the art, the microcontroller 60 typicallyincludes a microprocessor, or equivalent control circuitry, designedspecifically for controlling the delivery of stimulation therapy and mayfurther include RAM or ROM memory, logic and timing circuitry, statemachine circuitry, and I/O circuitry. Typically, the microcontroller 60includes the ability to process or monitor input signals (data) ascontrolled by a program code stored in a designated block of memory. Thedetails of the design and operation of the microcontroller 60 are notcritical to the present invention. Rather, any suitable microcontroller60 may be used that carries out the functions described herein. The useof microprocessor-based control circuits for performing timing and dataanalysis functions are well known in the art.

As shown in FIG. 2, an atrial pulse generator 70 and a ventricular pulsegenerator 72 generate pacing stimulation pulses for delivery by theright atrial lead 20, the right ventricular lead 30, and/or the coronarysinus lead 24 via an electrode configuration switch 74. It is understoodthat in order to provide stimulation therapy in each of the fourchambers of the heart, the atrial and ventricular pulse generators, 70and 72, may include dedicated, independent pulse generators, multiplexedpulse generators, or shared pulse generators. The pulse generators, 70and 72, are controlled by the microcontroller 60 via appropriate controlsignals, 76 and 78, respectively, to trigger or inhibit the stimulationpulses.

The microcontroller 60 further includes timing control circuitry 79which is used to control the timing of such stimulation pulses (e.g.,pacing rate, atrio-ventricular (AV) delay, atrial interconduction (A—A)delay, or ventricular interconduction (V—V) delay, etc.) evoked responsewindows, alert intervals, marker channel timing, etc., which is wellknown in the art. The switch 74 includes a plurality of switches forconnecting the desired electrodes to the appropriate I/O circuits,thereby providing complete electrode programmability. Accordingly, theswitch 74, in response to a control signal 80 from the microcontroller60, determines the polarity of the stimulation pulses (e.g., unipolar,bipolar, combipolar, etc.) by selectively closing the appropriatecombination of switches (not shown) as is known in the art.

Atrial sensing circuits 82 and ventricular sensing circuits 84 may alsobe selectively coupled to sense voltages between any of the electrodesof the right atrial lead 20, coronary sinus lead 24, and the rightventricular lead 30, and the can, through the switch 74 for sensing thepresence of cardiac activity in each of the four chambers of the heart.Accordingly, the atrial (ATR. SENSE) and ventricular (VTR. SENSE)sensing circuits, 82 and 84, may include dedicated sense amplifiers,multiplexed amplifiers, or shared amplifiers. The switch 74 determinesthe “sensing polarity” of the cardiac signal by selectively closing theappropriate switches, as is also known in the art. In this way, theclinician may program the sensing polarity independent of thestimulation polarity.

Each sensing circuit, 82 and 84, preferably employs one or more lowpower, precision amplifiers with programmable gain and/or automatic gaincontrol, bandpass filtering, and a threshold detection circuit, as knownin the art, to selectively sense the cardiac signal of interest. Theautomatic gain control enables the device 10 to deal effectively withthe difficult problem of sensing the low amplitude signalcharacteristics of atrial or ventricular fibrillation. The outputs ofthe atrial and ventricular sensing circuits, 82 and 84, are connected tothe microcontroller 60 which, in turn, are able to trigger or inhibitthe atrial and ventricular pulse generators, 70 and 72, respectively, ina demand fashion in response to the absence or presence of cardiacactivity in the appropriate chambers of the heart. The sensing circuits,82 and 84, in turn, receive control signals over signal lines, 86 and88, from the microcontroller 60 for purposes of controlling the gain,threshold, polarization charge removal circuitry (not shown), as isknown in the art.

Microcontroller 60 includes a vector-based cardiac event detection unit101, which operates to detect and classify cardiac electrical eventsbased on signal vectors generated from voltages received from the atrialand ventricular sense amplifiers, in accordance with a technique to bedescribed in detail below primarily with reference to FIGS. 5–9.

For arrhythmia detection, the device 10 utilizes cardiac event detectionunit 101 to sense cardiac signals to determine whether a rhythm isphysiologic or pathologic. As used herein “sensing” is reserved for thenoting of an electrical signal, and “detection” is the processing ofthese sensed signals and noting the presence of an arrhythmia. Thetiming intervals between sensed events (e.g., P-waves, R-waves, anddepolarization signals associated with fibrillation which are sometimesreferred to as “F-waves” or “Fib-waves”) are then classified by themicrocontroller 60 by comparing them to a predefined rate zone limit(i.e., bradycardia, normal, low rate VT, high rate VT, and fibrillationrate zones) and various other characteristics (e.g., sudden onset,stability, physiologic sensors, and morphology, etc.) in order todetermine the type of remedial therapy that is needed (e.g., bradycardiapacing, anti-tachycardia pacing, cardioversion shocks or defibrillationshocks, collectively referred to as “tiered therapy”).

Cardiac signals are also applied to the inputs of an analog-to-digital(A/D) data acquisition system 90. The data acquisition system 90 isconfigured to acquire intracardiac electrogram signals, convert the rawanalog data into a digital signal, and store the digital signals forlater processing and/or telemetric transmission to an external device102. The data acquisition system 90 is coupled to the right atrial lead20, the coronary sinus lead 24, and the right ventricular lead 30through the switch 74 to sample cardiac signals across any pair ofdesired electrodes.

The microcontroller 60 is further coupled to a memory 94 by a suitabledata/address bus 96, wherein the programmable operating parameters usedby the microcontroller 60 are stored and modified, as required, in orderto customize the operation of the stimulation device 10 to suit theneeds of a particular patient. Such operating parameters define, forexample, pacing pulse amplitude, pulse duration, electrode polarity,rate, sensitivity, automatic features, arrhythmia detection criteria,and the amplitude, waveshape and vector of each shocking pulse to bedelivered to the patient's heart 12 within each respective tier oftherapy. The operating parameters also include data packets specifyinginformation for use by cardiac event detection unit 101, including 1)events of interest for the particular patient in which the device isimplanted; 2) corresponding classification zones for each event ofinterest; and 3) a set of electrode pair combinations to be activatedvia switch 74 to sense signal vectors for comparison against theclassification zones.

Advantageously, the operating parameters of the implantable device 10may be non-invasively programmed into the memory 94 through a telemetrycircuit 100 in telemetric communication with the external device 102,such as a programmer, transtelephonic transceiver, or a diagnosticsystem analyzer. The telemetry circuit 100 is activated by themicrocontroller by a control signal 106. The telemetry circuit 100advantageously allows intracardiac electrograms and status informationrelating to the operation of the device 10 (as contained in themicrocontroller 60 or memory 94) to be sent to the external device 102through an established communication link 104.

In the preferred embodiment, the stimulation device 10 further includesa physiologic sensor 108, commonly referred to as a “rate-responsive”sensor because it is typically used to adjust pacing stimulation rateaccording to the exercise state of the patient. However, thephysiological sensor 108 may further be used to detect changes incardiac output, changes in the physiological condition of the heart, ordiurnal changes in activity (e.g., detecting sleep and wake states).Accordingly, the microcontroller 60 responds by adjusting the variouspacing parameters (such as rate, AV Delay, V—V Delay, etc.) at which theatrial and ventricular pulse generators, 70 and 72, generate stimulationpulses.

In addition, the stimulation device may be configured to performAutomatic Mode Switching (AMS) wherein the pacemaker reverts from atracking mode such as a VDD or DDD mode to a nontracking mode such asVVI or DDI mode. VDD, DDD, VVI and DDI are standard device codes thatidentify the mode of operation of the device. DDD indicates a devicethat senses and paces in both the atria and the ventricles and iscapable of both triggering and inhibiting functions based upon eventssensed in the atria and the ventricles. VDD indicates a device thatsensed in both chambers but only paces in the ventricle. A sensed eventon the atrial channel triggers a ventricular output after a programmabledelay, the pacemaker's equivalent of a PR interval. VVI indicates thatthe device is capable of pacing and sensing only in the ventricles andis only capable of inhibiting the functions based upon events sensed inthe ventricles. DDI is identical to DDD except that the device is onlycapable of inhibiting functions based upon sensed events, rather thantriggering functions. As such, the DDI mode is a non-tracking modeprecluding its triggering ventricular outputs in response to sensedatrial events. Numerous other device modes of operation are possible,each represented by standard abbreviations of this type.

The stimulation device additionally includes a battery 110, whichprovides operating power to all of the circuits shown in FIG. 2. For thestimulation device 10, which employs shocking therapy, the battery 110must be capable of operating at low current drains for long periods oftime, and then be capable of providing high-current pulses (forcapacitor charging) when the patient requires a shock pulse. The battery110 must also have a predictable discharge characteristic so thatelective replacement time can be detected. Accordingly, the device 10preferably employs lithium/silver vanadium oxide batteries, as is truefor most (if not all) current devices.

As further shown in FIG. 2, the device 10 is shown as having animpedance measuring circuit 112 which is enabled by the microcontroller60 via a control signal 114. The impedance measuring circuit 112 is notcritical to the present invention and is shown for only completeness.

In the case where the stimulation device 10 is intended to operate as animplantable cardioverter/defibrillator (ICD) device, it must detect theoccurrence of an arrhythmia, and automatically apply an appropriateelectrical shock therapy to the heart aimed at terminating the detectedarrhythmia. To this end, the microcontroller 60 further controls ashocking circuit 116 by way of a control signal 118. The shockingcircuit 116 generates shocking pulses of low (up to 0.5 joules),moderate (0.5–10 joules), or high energy (11 to 40 joules), ascontrolled by the microcontroller 60. Such shocking pulses are appliedto the patient's heart 12 through at least two shocking electrodes, andas shown in this embodiment, selected from the left atrial coilelectrode 28, the RV coil electrode 36, and/or the SVC coil electrode38. As noted above, the housing 40 may act as an active electrode incombination with the RV electrode 36, or as part of a split electricalvector using the SVC coil electrode 38 or the left atrial coil electrode28 (i.e., using the RV electrode as a common electrode).

Cardioversion shocks are generally considered to be of low to moderateenergy level (so as to minimize pain felt by the patient), and/orsynchronized with an R-wave and/or pertaining to the treatment oftachycardia. Defibrillation shocks are generally of moderate to highenergy level (i.e., corresponding to thresholds in the range of 5–40joules), delivered asynchronously (since R-waves may be toodisorganized), and pertaining exclusively to the treatment offibrillation. Accordingly, the microcontroller 60 is capable ofcontrolling the synchronous or asynchronous delivery of the shockingpulses.

Device Programmer Overview

FIG. 3 illustrates pertinent components of an external programmer foruse in programming an implantable medical device such as a pacemaker orICD. Briefly, the programmer permits a physician or other user toprogram the operation of the implanted device and to retrieve anddisplay information received from the implanted device such as IEGM dataand device diagnostic data. Additionally, the external programmerreceives and displays ECG data from separate external ECG leads that maybe attached to the patient. Depending upon the specific programming ofthe external programmer, programmer 200 may also be capable ofprocessing and analyzing data received from the implanted device andfrom the ECG leads to, for example, render preliminary diagnosis as tomedical conditions of the patient or to the operations of the implanteddevice.

Now, considering the components of programmer 200, operations of theprogrammer are controlled by a CPU 202, which may be a generallyprogrammable microprocessor or microcontroller or may be a dedicatedprocessing device such as an application specific integrated circuit(ASIC) or the like. Software instructions to be performed by the CPU areaccessed via an internal bus 204 from a read only memory (ROM) 206 andrandom access memory 230. Additional software may be accessed from ahard drive 208, floppy drive 210, and CD ROM drive 212, or othersuitable permanent mass storage device. Depending upon the specificimplementation, a basic input output system (BIOS) is retrieved from theROM by CPU at power up. Based upon instructions provided in the BIOS,the CPU “boots up” the overall system in accordance withwell-established computer processing techniques.

Once operating, the CPU displays a menu of programming options to theuser via an LCD display 214 or other suitable computer display device.To this end, the CPU may, for example, display a menu of specificprogramming parameters of the implanted device to be programmed or maydisplay a menu of types of diagnostic data to be retrieved anddisplayed. In response thereto, the physician enters various commandsvia either a touch screen 216 overlaid on the LCD display or through astandard keyboard 218 supplemented by additional custom keys 220, suchas an emergency VVI (EVVI) key. The EVVI key sets the implanted deviceto a safe VVI mode with high pacing outputs. This ensures lifesustaining pacing operation in nearly all situations but by no means isit desirable to leave the implantable device in the EVVI mode at alltimes.

Typically, the physician initially controls the programmer 200 toretrieve data stored within the implanted medical device and to alsoretrieve ECG data from ECG leads, if any, coupled to the patient. Tothis end, CPU 202 transmits appropriate signals to a telemetry subsystem222, which provides components for directly interfacing with theimplanted device, and the ECG leads. Telemetry subsystem 222 includesits own separate CPU 224 for coordinating the operations of thetelemetry subsystem. Main CPU 202 of programmer communicates withtelemetry subsystem CPU 224 via internal bus 204. Telemetry subsystemadditionally includes a telemetry circuit 226 connected to a telemetrywand 228, which, in turn, receives and transmits signalselectromagnetically from a telemetry unit of the implanted device. Thetelemetry wand is placed over the chest of the patient in the vicinityof the implanted device to permit reliable transmission of data betweenthe telemetry wand and the implanted device. Typically, at the beginningof the programming session, the external programming device controls theimplanted device via appropriate signals generated by the telemetry wandto output all previously recorded patient and device diagnosticinformation. Patient diagnostic information includes, for example,recorded IEGM data and statistical patient data such as the percentageof paced versus sensed heartbeats. Device diagnostic data includes, forexample, information representative of the operation of the implanteddevice such as lead impedances, battery voltages, battery recommendedreplacement time (RRT) information and the like. Data retrieved from theimplanted device is stored by external programmer 200 either within arandom access memory (RAM) 230, hard drive 208 or within a floppydiskette placed within floppy drive 210. Additionally, or in thealternative, data may be permanently or semi-permanently stored within acompact disk (CD) or other digital media disk, if the overall system isconfigured with a drive for recording data onto digital media disks,such as a write once read many (WORM) drive.

Once all patient and device diagnostic data previously stored within theimplanted device is transferred to programmer 200, the implanted devicemay be further controlled to transmit additional data in real time as itis detected by the implanted device, such as additional IEGM data, leadimpedance data, and the like. Additionally, or in the alternative,telemetry subsystem 222 receives ECG signals from ECG leads 232 via anECG processing circuit 234. As with data retrieved from the implanteddevice itself, signals received from the ECG leads are stored within oneor more of the storage devices of the external programmer. Typically,ECG leads output analog electrical signals representative of the ECG.Accordingly, ECG circuit 234 includes analog to digital conversioncircuitry for converting the signals to digital data appropriate forfurther processing within programmer. Depending upon the implementation,the ECG circuit may be configured to convert the analog signals intoevent record data for ease of processing along with the event recorddata retrieved from the implanted device. Typically, signals receivedfrom the ECG leads are received and processed in real time.

Thus, the programmer receives data both from the implanted device andfrom the external ECG leads. Data retrieved from the implanted deviceincludes parameters representative of the current programming state ofthe implanted device. Under the control of the physician, the externalprogrammer displays the current programming parameters and permits thephysician to reprogram the parameters. To this end, the physician entersappropriate commands via any of the aforementioned input devices and,under control of CPU 202, the programming commands are converted tospecific programming parameters for transmission to the implanted devicevia telemetry wand 228 to thereby reprogram the implanted device. Priorto reprogramming specific parameters, the physician may control theexternal programmer to display any or all of the data retrieved from theimplanted device or from the ECG leads, including displays of ECGs,IEGMs, and statistical patient information. Any or all of theinformation displayed by programmer may also be printed using a printer236.

CPU 202 includes a vector-based event detection set-up unit 250 forgenerating data packets specifying information for use by thevector-based cardiac event detection unit of the implanted device (101of FIG. 2), including 1) events of interest for the particular patientin which the device is implanted; 2) corresponding classification zonesfor each event of interest; and 3) a set of electrode pair combinationsto be activated within the device to sense signal vectors for comparisonagainst the classification zones. The operation of set-up unit 250 isdescribed in detail below primarily with reference to FIGS. 10 and 11.

Programmer 200 also includes a modem 238 to permit direct transmissionof data to other programmers via the public switched telephone network(PSTN) or other interconnection line, such as a T1 line or fiber opticcable. Depending upon the implementation, the modem may be connecteddirectly to internal bus 204 may be connected to the internal bus viaeither a parallel port 240 or a serial port 242. Other peripheraldevices may be connected to the external programmer via parallel port240 or a serial port 242 as well. Although one of each is shown, aplurality of input output (10) ports might be provided.

A speaker 244 is included for providing audible tones to the user, suchas a warning beep in the event improper input is provided by thephysician. Telemetry subsystem 222 additionally includes an analogoutput circuit 246 for controlling the transmission of analog outputsignals, such as IEGM signals output to an ECG machine or chartrecorder.

With the programmer configured as shown, a physician or other useroperating the external programmer is capable of retrieving, processingand displaying a wide range of information received from the ECG leadsor from the implanted device and to reprogram the implanted device ifneeded. The descriptions provided herein with respect to FIG. 3 areintended merely to provide an overview of the operation of programmerand are not intended to describe in detail each and every feature of thehardware and software of the device and is not intended to provide anexhaustive list of the functions performed by the device.

Event Classification Technique Overview

Briefly, sense amplifiers of the implanted device sense voltages betweenvarious combinations of electrodes and the signal vector event detectionunit generates a signal vector based on the voltages. The eventdetection unit compares the signal vector with a set of classificationzones specified by an input zone classification kernel. Theclassification zones each correspond to a different event of interest,such as a P-wave, R-wave, T-wave, A-pulse, V-pulse, PAC, or PVC. Theevent detection unit determines whether the signal vector lies withinany of the classification zones. If the signal vector lies within aclassification zone, such as within the P-wave classification zone, theevent associated with the signal vector is thereby identified inaccordance with the zone in which it lies. If the signal vector does notlie with any of the classification zones, the event is designated as anunclassified event, which may be electrical noise. Once the event hasbeen identified, the microcontroller of the implanted device responds,as needed, to perhaps calculate a new heart rate, modifying pacingtherapy, or store diagnostic information.

More specifically, since voltage is measured as the difference inpotential between any two points, a voltage can be measured between anycombination of the electrodes of FIG. 1 and between those electrodes andthe device can. FIG. 4 illustrates a specific example of switchingcircuit 74 (of FIG. 2) wherein the device senses signals only betweenthe A-tip, A-ring, left V-tip, left V-ring, atrial coil and device can,thus generating fifteen different voltage signals, numbered 1–15. Theadditional electrodes available in the bi-ventricular device of FIG. 1permit more combinations of electrode pairs. The fifteen signalsdepicted in FIG. 4 are shown for illustrative purposes only.

Consider signals 1, 4, 5, 8, 9, 10, 12, 14, and 15 of FIG. 4. Values a₁through a₉ represent the voltage amplitude values of these nine signals,as shown in TABLE I:

TABLE I AMPLITUDE ELECTRODE VALUE SIGNAL COMBINATION a₁ 1 A-TIP TO CANa₂ 4 A-TIP TO V-TIP a₃ 5 A-TIP TO A-RING a₄ 8 A-RING TO V-RING a₅ 9A-RING TO V-TIP a₆ 10 V-TIP TO CAN a₇ 12 V-TIP TO V-RING a₈ 14 V-RING TOCOIL a₉ 15 COIL TO CAN

Taken together, the signals are represented as a vector, [a₁, . . . ,a₉], abbreviated as _(A). The specific values of a₁ through a₉ typicallyvary significantly for different types of cardiac events, such asP-waves or R-waves, as each signal, or vector element, senses the eventfrom a different location. In a P-wave, for example, the a₃ component istypically the strongest, with the a₁ component the next strongest, thea₂, a₄, and as components at various strengths less than a₁, and theremaining components having various strengths even less than those ofa₂, a₄, and a₅. In an R-wave, a₇ and a₈ typically are the strongest, a₆and a₉ are next strongest, a₂, a₄, and as are weaker, and a₁ and a₃ arethe weakest. Thus, each different type of cardiac event, i.e., eventtype, evokes signal vectors characteristic of that event type. It hasbeen found that signal vectors evoked by a given event type clusterwithin a geometric region characteristic of that event type, asillustrated by the simplified three-dimensional representation in FIG.5, which shows only the a₁, a₂, and a₃ signal components. Such regionsare referred to herein as classification zones. Each event type, e.g.,P-wave, A-wave, R-wave, V-wave, etc., has its own, unique classificationzone. Note that the three-dimensional representation of FIG. 5 is merelyillustrative of the concepts involved. No multi-dimensional graphicrepresentations need be generated to actually implement the invention.

For any given implantable medical device, e.g., dual-chamberdefibrillator, single chamber pacer, etc., certain event types are ofinterest to that device. For each of these event types, a correspondingclassification zone is generated (by techniques described below) thatcorrelates to that event type. The resulting set of classification zonescorrelating to the event types of interest for a particular device isreferred to herein as the kernel for that device. In a dual chamberpacemaker, for example, if the event types of interest are P-waves,A-waves, R-waves, and V-waves, then the kernel consists of theclassification zones Z_(p), Z_(a), Z_(r), and Z_(v) that correlate toP-waves, A-waves, R-waves, and V-waves, respectively. The classificationzones are patient specific and are therefore preferably customized, ormodeled, individually for each patient. An exemplary method for modelingthe kernel for a specific device and patient is described below.

Once the kernel for a particular device and patient has been modeled,the kernel serves as a key for classifying individual events, or eventinstances, sensed in that patient. Each event instance produces a signalvector for comparing with the classification zones which, as noted,correlate to specific event types. The event instance is therebyclassified. Using the above example, if event instance E produces signalvector A, then A is compared to each of the classification zones {Z_(p),Z_(a), Z_(r), Z_(v)}in the kernel. If A matches Z_(a), then E isclassified as an A-wave.

As noted, signal vectors produced by event instances of a given eventtype cluster within a region, or zone, that is characteristic of thatevent type. The cluster exhibited by an event type is reduced to amathematical model that approximates and contains the cluster andthereby defines the classification zone correlating to the event type.Repeating this process for each event type of interest yields a model ofeach of the classification zones in the kernel. Any one of severalpossible mathematical models may be used for this purpose. An exemplarymodel is described below. To maximize flexibility in setting safetymargins and to minimize the possibility of inconclusive classifications,it is desirable to maximize the separation between the clusterscharacteristic of different event types.

Consider again the example of TABLE I above wherein values a₁ through a₉represent signal sources 1, 4, 5, 8, 9, 10, 12, 14, and 15,respectively. This produces a nine-dimensional vector space withindividual vectors comprised of values from signal sources 1, 4, 5, 8,9, 10, 12, 14, and 15. However, this combination of signal sources isonly one example; many different combinations of signal sources arepossible. As another example, values a₁ through a₇ could representsignal sources 1, 3, 5, 6, 11, 13, and 14, respectively, giving rise toa seven-dimensional vector space. The specific combination, or subset,of signal sources being used for a given device is referred to herein asthe signal space.

Separation is visualized three dimensionally as spatial separation, ascan be seen from comparing the smaller separation of FIG. 5 with thelarger separation in FIG. 6. More specially, FIG. 5 illustrates therelatively small separation between intrinsic R-wave and paced V-waveclusters expected within the signal space comprised of signals 4 (A-tipto V-tip), 5 (A-tip to A-ring), and 6 (A-ring to Can). FIG. 6illustrates the relatively larger separation between R-wave and V-waveclusters expected within the signal space comprised of signals 7 (A-ringto Coil), 8 (A-ring to V-ring), and 10 (V-tip to Can).

The amount of separation between clusters is, to some degree, a functionof signal space. Selecting a signal space that maximizes the separationbetween clusters is a part of the modeling process described below.Preferably, the implanted device is configured to provide access to allthe signal sources possible for the device and the software embedded inthe device is configured to enable the clinician to customize the subsetof signal sources, i.e., the signal space, to be used for a givenpatient and device.

With kernel modeling it is preferred that event instances, and theirobserved signal vectors, be grouped according to event type so that theresulting clusters can be used to define classification zones. Thisrequires that each event instance be classified according to its eventtype. Classification zones are not used in the modeling process becausethey are not defined until after the modeling process is complete.Therefore, an external frame of reference for classifying eventinstances is used during the modeling process. The surface ECG providessuch a frame of reference. By synchronizing to the surface ECG, eachevent instance can be classified according to the surface ECG indicationat the time that event instance occurred.

In the preferred implementation, the classification zone is representedas an aggregate of two components: a direction vector and a geometricrange. The geometric range component, in turn, is an aggregateconsisting of a maximum angle relative to the direction vector and aminimum and maximum length. This representation of classification zonesis visualized in three-dimensional space as truncated conical sections,as depicted in FIG. 7.

To model the classification zone for an event type, the constituentcomponents of the classification zone—direction vector and geometricrange—are generated from a cluster of signal vectors measured for thatevent type. The direction vector is the average of the individual signalvectors. If (a_(1,1), a_(1,2), . . . , a_(1,9)), (a_(2,1), a_(2,2), . .. , a_(2,9)), . . . , (a_(n,1), a_(n,2), . . . , a_(n,9)) represent nmeasurements taken from nine electrode pairs of TABLE I, then theaverage, {dot over (α)}, or (α₁, α₂, . . . , α₉), is given by$\quad\begin{matrix}{\overset{.}{\alpha} = \left( {\alpha_{1},\alpha_{2},\ldots\mspace{14mu},\alpha_{9}} \right)} \\{= \left\lbrack {\frac{\left( {a_{1,1} + a_{2,1} + \ldots + a_{n,1}} \right)}{n},\frac{\left( {a_{1,2} + a_{2,2} + \ldots + a_{n,2}} \right)}{n},\ldots\mspace{14mu},} \right.} \\{\left. \frac{\left( {a_{1,9} + a_{2,9} + \ldots + a_{n,9}} \right)}{n} \right\rbrack.}\end{matrix}$

For a generalized system employing m electrode pairs, with (a_(1,1),a_(1,2), . . . , a_(1,m)), (a_(2,1), a_(2,2), . . . , a_(2,m)), . . . ,(a_(n,1), a_(n,2), . . . , a_(n,m)) representing n measurements, thenthe average, {dot over (α)}, or (α₁, α₂, . . . , α_(m)), is given by$\quad\begin{matrix}{\overset{.}{\alpha} = \left( {\alpha_{1},\alpha_{2},\ldots\mspace{14mu},\alpha_{m}} \right)} \\{= \left\lbrack {\frac{\left( {a_{1,1} + a_{2,1} + \ldots + a_{n,1}} \right)}{n},\frac{\left( {a_{1,2} + a_{2,2} + \ldots + a_{n,2}} \right)}{n},\ldots\mspace{14mu},} \right.} \\{\left. \frac{\left( {a_{1,m} + a_{2,m} + \ldots + a_{n,m}} \right)}{n} \right\rbrack.}\end{matrix}$

The geometric range component of the classification zone consists of amaximum angle relative to the direction vector, a minimum length, and amaximum length. The minimum and maximum lengths are determined bycomputing the norm, or length, of each of the individual signal vectors.The smallest norm, less some safety margin, becomes the minimum lengthand the largest norm, plus some safety margin, becomes the maximumlength. Similarly, the maximum angle is determined by computing theangle between each signal vector, α_(i), and the average vector, {dotover (α)}. The largest of these values, plus some safety margin, becomesthe maximum angle relative to the direction vector. The angle betweena_(i) and {dot over (α)} is given by the following formula:θ=cos⁻¹[(a _(i) {dot over (α)})/(∥a _(i)∥∥α∥]

-   -   where a_(i){dot over (α)} is the dot-product, or inner product,        of a_(i) and {dot over (α)}_(i), given by        (a_(i,1))(ã₁)+(a_(i,2))(ã₂)+ . . . +(a_(i,m))(ã_(m))        ∥a_(i)∥ is the norm of a_(i), given by        (a_(i1) ²+a_(i2) ²+ . . . +a_(im) ²)^(1/2)    -   and ∥{dot over (α)}∥ is the norm of {dot over (α)}.

This is represented using the following notationZ _(i)={α_(i), θ_(i) , I _(i) , L _(i)}

-   -   where Z_(i) is a classification zone and α_(i), θ_(i), I_(i),        and L_(i) represent the direction vector, maximum angle, minimum        length, and maximum length, respectively. FIG. 8 illustrates        these geometric parameters in three-dimensional space.

Given this model, an event instance is then classified by matching itsresulting signal vector to a classification zone. This is accomplishedby comparing the signal vector to each classification zone in thekernel. A classification zone, Z_(i)={{dot over (α)}_(i), θ_(i), l_(i),L_(i)}, is said to match, or contain, signal vector A ifI _(i) <=∥A∥<=L _(i)  (1)and(A·{dot over (α)})/(∥A∥∥{dot over (α)}∥)<=cos θ_(i)  (2)

When a signal vector is compared to a classification zone, allcomponents of the signal vector are used in the comparison. Therefore,none of those components need be ignored or suppressed by employingrefractory or blanking periods. Stated another way, once a signal spacehas been selected for a kernel, all constituent signals of that signalspace are used in the classification process without the need forrefractory or blanking periods.

Individual Event Classification Method

Specific steps taken by the implanted device to implement the techniqueoutlined above will now be described with reference to FIG. 9.Initially, at step 300, the vector-based cardiac event detection unit ofthe implanted device inputs a zone classification packet from theexternal programmer that specifies: 1) events of interest for theparticular patient in which the device is implanted; 2) correspondingclassification zones for each event of interest; and 3) a set ofelectrode pair combinations to be used by the device to sense signalvectors for comparison against the classification zones. The zoneclassification packet is a package of data that encodes the foregoinginformation in numerical form, in accordance with conventional computertechniques. Preferably, the zone classification packet is configured torepresent the classification zones using the kernel-based techniquedescribed above, but may alternatively be configured to specifyclassification zones using other techniques as well. TABLE IIillustrates the data provided in an exemplary zone classificationpacket.

TABLE II EVENTS OF INTEREST CLASSIFICATION ZONE P-WAVE P-WAVE ZONE:P-WAVE DIRECTION VECTOR P-WAVE MINIMUM LENGTH P-WAVE MAXIMUM LENGTHP-WAVE MAXIMUM ANGLE R-WAVE R-WAVE ZONE: R-WAVE DIRECTION VECTOR R-WAVEMINIMUM LENGTH R-WAVE MAXIMUM LENGTH R-WAVE MAXIMUM ANGLE T-WAVE T-WAVEZONE: T-WAVE DIRECTION VECTOR T-WAVE MINIMUM LENGTH T-WAVE MAXIMUMLENGTH T-WAVE MAXIMUM ANGLE A-PULSE A-PULSE ZONE: A-PULSE DIRECTIONVECTOR A-PULSE MINIMUM LENGTH A-PULSE MAXIMUM LENGTH A-PULSE MAXIMUMANGLE V-PULSE V-PULSE ZONE: V-PULSE DIRECTION VECTOR V-PULSE MINIMUMLENGTH V-PULSE MAXIMUM LENGTH V-PULSE MAXIMUM ANGLE ELECTRODE PAIRSA-TIP TO CAN V-TIP TO CAN A-TIP TO V-TIP V-TIP TO V-RING A-TIP TO A-RINGV-RING TO COIL A-RING TO V-RING COIL TO CAN A-RING TO V-TIP

The events of interest specified in the packet typically include, asshown in the table, P-waves, R-waves, T-waves, A-pulses, and V-pulses,and may additionally include other electrical cardiac events, such asPAC's, PVCs, and the like. In general, each and every type of event thatthe implanted device must detect in order to administer therapy isspecified. Additionally, events of purely diagnostic interest may bespecified. Rather than specify the events of interest in the packet, thelist of events may be preprogrammed into the device at devicemanufacture. In such case, the kernel need only specify theclassification zones associated with the pre-programmed events ofinterest.

In the example, of TABLE II, each zone is a representative of atruncated multi-dimensional cone defined in terms of direction, vector,minimum length, maximum length, and maximum angle, in accordance withthe mathematical model detailed above. However, alternative techniquesmay be employed for specifying the classification zones. Indeed,different shaped zones may be employed for the various event types. Forexample, the P-wave zone may be represented as a multidimensional spherespecified by a center point and a radius, whereas the R-wave zone may berepresented as a multidimensional ellipsoid specified by a center pointand an appropriate number of semi-axes. The use of truncated cones ispreferred as it is relatively easy to implement but, in general, anyappropriate geometric zone shape or shapes can be used so long as theypermit cardiac events to be uniquely identified. Multiple zones perevent can also be specified with, for example, a first set of zones usedas a primary set for classifying events and a second set employed forevents deemed unclassifiable using the first set of zones. Or differentzones can be used based on the current mode of operation of the deviceor condition of the patient. For example, one set of zones might be usedwhile the device is in a tracking mode and another in a non-trackingmode or one set might be used while the patient is at rest and anotherwhile active. Similarly, whereas the example of TABLE II provides asingle set of electrode pairs for use in detecting all events, multiplesets of electrode pairs can alternatively be specified. Again, a firstset might be used as a primary set for classifying events and a secondset employed for events deemed unclassifiable using the first set ofelectrode pairs. As can be appreciated, a wide range of alternativeembodiments may be implemented consistent with the general principles ofthe invention and no attempt is made herein to itemize all possiblevariations.

At step 302, the event detection unit controls the implanted device toactivate sense amplifiers associated with the electrode pairs specifiedin the zone classification packet and, at step 304, begins receivingvoltage signals from the pairs of electrodes. The voltages changecontinuously with time. Whenever the voltages exceed some predeterminedthreshold, indicative of a possible cardiac electrical event, thevoltages are sampled and a signal vector is generated at step 306. Inone implementation, voltages from all of the selected electrode pairsare converted to positive voltages then combined, and a signal vector isgenerated only if the combined voltage exceeds a threshold voltage. Inanother implementation, each separate voltage is compared against athreshold voltage and a signal vector is generated whenever any of thevoltages exceeds its respective threshold voltage. Once the thresholdhas been exceeded, indicative of a possible cardiac electrical event,the analog voltages are converted to digital values usinganalog-to-digital (A-to-D) converters, and the digital values are thenstored internally within a data array having a separate numerical valuefor each electrode pair. Thus the signal vector is a numericalrepresentation of a possible cardiac electrical event occurring in theheart, which may be, for example, a P-wave or R-wave. At step 308, thesignal vector is compared with the set of classification zones in anattempt to classify the event.

In still other implementations, rather than comparing electrode pairvoltages against threshold voltages, the voltages are first converted todigital values to yield a signal vector. The signal vector is thencompared against a numerical threshold and, if it does not exceed thethreshold, the signal vector is discarded. Only signal vectors thatexceed the numerical threshold are compared, at step 308, with the setof classification zones in an attempt to classify the event. In onespecific implementation, the numerical threshold is defined as thesmallest of the minimum lengths of each of the classification zones. Ifthe length of the signal vector is smaller than the numerical thresholdvalue, it will necessarily be smaller than the minimum length for anyclassification zone and will therefore not yield a classifiable event.Alternative threshold comparison techniques may be employed as well. Thespecific technique that is most effective may be determined via routineexperimentation.

In any case, as noted, the signal vector is compared at step 308 withthe set of classification zones in an attempt to classify the event. Thecomparison at step 308 is performed by sequentially comparing eachclassification zone with the signal vector until a classification zoneis found that matches the vector. If using the mathematical modeldescribed above, classification zone, Z_(i)={{dot over (α)}_(i), θ_(i),I_(i), L_(i)}, is said to match, or contain, signal vector A ifI_(i)<=∥A∥<=L_(i) and (A·{dot over (α)})/(∥A∥∥{dot over (α)}∥)<=cosθ_(i). Each of the forgoing mathematical values is internallyrepresented using data variables or arrays and the mathematicalcomparisons are performed in accordance with otherwise conventionalcomputing techniques.

If the signal vector matches one of the classification zones, theelectrical event in the heart represented by the signal vector isclassified based on the zone at step 310. Thus, if the signal vectormatched the P-wave zone, the event is classified as a P-wave; if thesignal vector matched the R-wave zone, the event is classified as aR-wave; and so on. The zones are mutually exclusive so that a signalvector will match, at most, one and only one zone. If the signal vectordoes not match any of the classification zones, the electrical event isdeemed to be unclassified, at step 312, and diagnostic data is storedidentifying the unclassified event. The event may represent noise.During a follow-up session with the physician, the diagnostic data maybe reviewed and, if the number of unclassified events exceeds somethreshold, the physician may be prompted to modify the electrodecombination or to specify additional events of interest. In any case,step 314 is then performed wherein the event detection unit forwards theresults of the classification process to the microcontroller for use incontrolling operations of the implanted device to, for example,administer cardiac pacing or defibrillation therapy to the patient or tostore diagnostic information. Processing then immediately returns tostep 304 to sense and classify the next event.

Steps 304 to 314 are performed continuously in a loop at all times whilethe implanted device is operating within the patient to continuouslydetect cardiac events, if any, and deliver appropriate therapy. Notethat the microcontroller does not typically base therapy deliverydecisions on detection of a single event but on information gained froma collection of events. For example, the detection of several R-waveswithin a given period of time permits the microcontroller to determinethe heart rate of the patient, which may then trigger delivery ofcardioversion shocks if the heart rate exceeds some threshold. Hence, itmay be necessary to detect a number of events using steps 304–314 beforetherapy is actually delivered. In general, the microcontroller processesthe event classification information provided by the vector-based eventdetection using otherwise conventional techniques. No attempt is madeherein to describe such processing in detail.

Exemplary Classification Zone Generation Method

Specific steps performed to set-up the classification zones will now bedescribed with reference to the FIGS. 10 and 11. The set-up method ispreferably performed immediately following implant of the device as theimplanted device is not able to detect cardiac signals until set-up hasbeen performed. Alternatively, default classification zones arepre-programmed into the device to permit the device to begin operatingimmediately, and the set-up method is performed later to “fine tune” theclassification zones for the particular patient. In any case, theclassification zones are generated by the vector-based event detectionset-up unit of the external programmer using signals receivedsimultaneously from the implanted device and from a surface ECG unitstrapped to the chest of the patient. Steps performed by the surface ECGunit, the external programmer and the implanted device are shown on theleft, middle and right sides of FIG. 10, respectively. At step 400, theexternal programmer inputs a list of cardiac events of interest for thepatient from the physician or other clinician operating the externalprogrammer. The selection of the events depends, in part, on theparticular condition of the patient such as any chronic dysrhythmias.The list of events typically includes, at least, P-waves, R-waves,T-waves, A-pulses, and V-pulses but may additionally include otherevents, such as PAC's, PVCs, and the like, deemed important by thephysician. At minimum, every event the implanted device must detect inorder to be able to make therapy delivery decisions must be specified.Additionally, events that are merely of diagnostic interest may also bespecified. Preferably, the external programmer is configured to generatea default list of events based on the capabilities of the implanteddevice and based on whatever other programming commands have beenspecified by the physician (such as whether the physician has enableoverdrive pacing or the like). The default list is presented to thephysician for review and the physician can then expand the list if sodesired. Alternatively, the implanted device is preprogrammed with afixed list of detectable events, which the external programmer retrievesfrom the implanted device via telemetric interrogation. If so, no userinput from the physician is required, though the programmer ispreferably configured to present the list to the physician, ifrequested.

Based on the list of events to be detected by the implanted device, theprogrammer then retrieves, at step 402, a pre-stored list of thepreferred or optimal combinations of electrode pairs needed to detectthe events. For example, if the list of events includes only P-waves,R-waves, T-waves, A-pulses, and V-pulses, the optimal combination ofelectrodes may specify the following combination of electrode pairs asthe optimal combination: A-tip to can, A-tip to V-tip, A-tip to A-ring,A-ring to V-ring, A-ring to V-tip, V-tip to can, V-tip to V-ring, V-ringto coil, and coil to can. If the list of events additionally includesPAC's, PVCs, the optimal combination of electrodes may specifyadditional electrode pairs. The list of optimal electrode pairs alsodepends on the particular capabilities of the implanted device and thearrangement of leads. Thus, for a particular combination of events to bedetected, one set of optimal electrode pairs may be specified for usewith bipolar pacing leads whereas another set is specified for use withmonopolar leads. The list of optimal electrode pairs may also dependupon the characteristics of the patient such as gender, age, weight,generally activity level, chronic dysrhythmias etc.

The optimal combinations of electrode pairs may be determined in advancebased on a statistical analysis of the distribution of signal vectorsfor each of type of cardiac events taken from a population of patients.More specifically, for each detectable event, signal vectors from apopulation of patients are detected and analyzed to determine thespecific combination of electrodes that provides the optimal clusteringof signal vectors to permit the most reliable event detection. Theoptimal cluster is typically one wherein events of the same type (suchas P-waves) always yield a closely-adjacent clustering of signal vectorsregardless of heart rate, gender, age, etc. but wherein events ofdiffering types (such as P-waves vs. R-waves) always yield a widecluster separation, also regardless of heart rate, gender, age, etc. Inthis manner, electrode combinations are identified that can be reliablyused to discriminate among the different types of events regardless ofheart rate, gender, age, etc. The optimal electrode combinations arethen pre-programmed into the external programmer for use with the methodof FIG. 10. If two or more electrode combinations are equally effectivein discriminating among the events (i.e. the cluster separations aregenerally the same), the combination requiring the fewest number ofelectrode pairs is preferred, so as to reduce the processing burdenwithin the implanted device. If different electrode combinations are tobe employed depending upon the characteristics of the patient, studiesare performed on populations of patients having differingcharacteristics, such as different age groups, genders etc., to permitthe determination of a set of optimal electrode combinations. In thismanner, different optimal electrode combinations may be generated foruse with different age groups, genders, etc. As can be appreciated, awide range of techniques are available for determining and specifyingoptimal electrode combinations consistent with the principles of theinvention and no attempt is made herein to list all possible techniques.In general, the studies employed to determine the optimal electrodecombinations may be performed in accordance with routine experimentaltechniques using routine statistical analysis techniques and,accordingly, will not be described in further detail herein.

Beginning, at step 404, the external programmer activates the surfaceECG unit to begin collecting surface ECG data (at step 406), which istransmitted to the external programmer (at step 408) for storagetherein. Also at step 404, the external programmer controls theimplanted device to begin generating signal vectors (at step 410), whichare also transmitted to the external programmer (at step 412) forstorage therein. Thus, surface ECGs and signal vectors are collectedsimultaneously from the patient and hence represent the same electricalevents within the heart of the patient. Data is collected over a periodof time, typically at least a half hour, to thereby obtain astatistically significant amount of data from which classification zonescan be generated. Within a half hour, about 1800 samples can becollected (30 minutes times approximately 60 beats per minute). Lessfrequent events, such as PVCs, do not occur with nearly that frequencybut can be induced in the patient so as to permit collection of thenecessary event samples. Preferably, the patient is asked to exerciseduring a portion of this time and to rest during a portion of this timeto obtain data for a variety of exercise states, although this may notbe feasible if the device has just been implanted.

Once a sufficient amount of data has been obtained, the set-up unit ofthe external programmer, at step 414, identifies the various cardiacevents appearing in the ECG using conventional techniques, i.e. P-waves,R-waves, etc. are identified. The set-up unit then labels the signalvectors that had been simultaneously detected by the implanted devicebased on the identity derived from the ECG. In other words, all signalvectors detected during P-waves are labeled as P-wave signal vectors;all signal vectors detected during R-waves are labeled as R-wave signalvectors; and so on. Labeling is achieved by storing appropriateidentification values along with the signal vector data already storedin memory. Note that not all signal vectors are labeled. Only signalvectors that correspond to events detected within the ECG are labeled.Signal vectors detected during quiet periods between electricallysignificant events are not labeled since no corresponding event isdetected in the ECG. Likewise, signal vectors corresponding toelectrical noise are not labeled.

The set-up unit then processes the labeled signal vectors, at step 416,to generate unique classification zones for the various event types.This involves determining a geometric range for each classificationzone, which will be described with reference to FIG. 11. Once theclassification zones have been determined, data specifying the zones isassembled into the classification zone data packet along with a list ofthe events of interest and the optimal electrode combinations andtransmitted to the implanted device, at step 418. The physician thencontrols the implanted device to commence identifying cardiac events(step 419) using the new classification zones in accordance with themethod of FIG. 9. If a previous set of classification zones has alreadybeen programmed into the implanted device, the new set replaces theolder set. Although not shown in FIG. 11, preferably, the physicianverifies that the implanted device is correctly identifying cardiacevents. This may be achieved by controlling the external programmer toreceive and process surface ECG signals and controlling the implanteddevice to begin transmitting IEGM signals, with the cardiac events(identified using the new classification zones) labeled therein. Theexternal programmer then identifies the events based on the surface ECGsignals and compares with the event-identification labels provided bythe implanted device to verify correct operation of the device. If theimplanted device is not correctly identifying cardiac events using thenew zone classifications, appropriate steps may be taken such asrepeating the steps of FIG. 11 to generate a new set of classificationzones or reloading default classification zones originally programmedinto the implanted device.

Referring now to FIG. 11, the method by which the geometric ranges ofthe classification zones are derived within step 416 of FIG. 10 will nowbe described. At step 420, the set-up unit selects the first event fromthe list of events of interest originally input at step 400 of FIG. 10.In this example, it will be assumed that the first event is a P-wave. Atstep 422, all signal vectors that had been labeled (at step 414 of FIG.10) as corresponding to P-waves are then retrieved from memory. Thesignal vectors are then averaged together at step 424 to determine thedirection vector for the P-wave classification zone. At steps 426 and428, the minimum and maximum vector lengths for the P-waveclassification zone are generated by identifying, respectively, theshortest and longest individual P-wave signal vectors. At step 430, themaximum vector angle for the zone is determined. These geometricalfeatures are shown in FIG. 8 and the mathematical calculations fordetermining the geometrical features are described above in connectionwith the descriptions of FIG. 8.

Hence, steps 422–430 operate to generate a P-wave classification zonebased on the cluster of P-wave signal vectors generated by the implanteddevice during the steps 410 and 412 of FIG. 10. The size of theclassification zone is just sufficient to enclose all of the P-wavesignal vectors. However, additional valid P-wave signal vectors may fallslightly outside the classification zone. At step 434, the size of theclassification zone is expanded to thereby provide a safety marginsufficient to ensure that additional valid P-waves also fall within theclassification zone and hence will be properly classified as P-waves.The classification zone is expanded by decreasing the minimum vectorlength, increasing the maximum vector length and increasing the maximumvector angle, by predetermined percentages, perhaps 20–30%. Preferably,the precise percentage amount of the safety margin is determined viaroutine experimentation, and may vary from patient to patient. In thealternative, classification zones may be “trimmed” to tighterboundaries, depending on their clustering relative to one another, byusing statistical 3-sigma or 4-sigma values for θ_(i), I_(i), and L_(i)instead of safety margins.

The process of steps 420–432 are repeated for each additional selectedevent type to thereby generate classification zones for those eventtypes as well. In the exemplary technique of FIG. 11, eachclassification zone is specified as a multidimensional truncated zone.However, as noted above, in other examples, each zone has a differentgeometric shape and so different calculation techniques are employedwithin steps 420–432 for each event type. In any case, onceclassification zones have been generated for all selected event types,the set-up unit verifies, at step 434, that none of the classificationzones overlap, then stores the resulting geometric zones at step 436within the patient classification zone data packet. In the extremelyunlikely event that any of the classification zones overlap, then asignal vector lying within the overlapping region would not be properlyclassifiable. So if any overlap is detected, a warning signal isgenerated (and an appropriate screen is presented on the display screenof the external programmer) to alert the physical of the problem, whichmight be correctable by selecting a different combination of electrodepairs and repeating the steps of FIGS. 10 and 11 to generate newclassification zones based on the new electrode combinations. Again, thezones are examined to verify that no overlap occurs.

In an alternative technique, rather than retrieving a list of optimalelectrode combinations at step 402 of FIG. 10, the set-up unit initiallycontrols the implanted device to activate all electrode pairs and togenerate signal vectors based on all electrode pairs. The set-up unitthen generates classification zones using the method of FIG. 11 for allor selected combinations of the electrodes pairs. The set-up unit thenselects the combination of electrode pairs that provides the greatestseparation of classification zones to thereby provide for the mostreliable event classification while also eliminating any overlapproblems.

Event Sequence Classification Method

FIG. 12 illustrates an alternative method wherein entire sequences ofevents are detected rather than individual events. The sequence-basedmethod is similar to the single event-based method of FIG. 9 and onlypertinent differences will be described in detail. At step 500, theimplanted device inputs a sequence-based zone classification packet fromthe external programmer that specifies: 1) sequences of events ofinterest for the particular patient; 2) corresponding sequences ofclassification zones; and 3) a set of electrode pair combinations to beused by the device to sense signal vectors for comparison against theclassification zones. Exemplary sequences include a normal sinus beat orPVC. In general, each and every event sequence that the implanted devicemust detect in order to administer therapy is specified. Additionally,events of purely diagnostic interest may be specified.

At step 502, the event detection unit controls the implanted device toactivate sense amplifiers associated with the electrode pairs specifiedin the sequence-based zone classification packet and, at step 504,begins receiving voltage amplitude signals from the pairs of electrodes.A sequence of signal vectors is generated from the sampled voltages and,once a sufficient number of signal vectors are detected then, at step506, the sequence of signal vectors is compared against theclassification zone sequences. To determine when a sufficient number ofsignal vectors have been detected, the device may employ a timer or acounter for counting the number of signal vectors detected. Also at step506, the sequence of signal vectors is compared with the set ofclassification zone sequences to classify the sequence of events. Thecomparison at step 506 is performed by sequentially comparing each setof classification zone sequences with the sequence of signal vectorsuntil a match is found. If the sequence of signal vectors matches one ofthe classification zone sequences, the electrical event in the heartrepresented by the sequence of signal vectors is classified based on thezone sequence at step 508. Thus, if the sequence of signal vectorsmatched the normal sinus beat zone sequence, the sequence of events isclassified as a normal sinus beat and so on. If the sequence of signalvectors does not match any of the classification zone sequences, theelectrical event is deemed to be unclassified, at step 510, anddiagnostic data is stored identifying the unclassified event. In anycase, step 512 is then performed wherein the event detection unitforwards the results of the classification process to themicrocontroller for use in controlling operations of the implanteddevice to, for example, administer cardiac pacing or defibrillationtherapy to the patient or to store diagnostic information. Processingthen immediately returns to step 504 to sense and classify the nextevent.

Thus FIG. 12 sets forth a sequence-based detection technique similar tothe single event-base detection technique of FIG. 9. Depending upon theprogramming of the system, both techniques may be implanted together,thus providing two-levels of event detection. In addition to detectingevents such as P-waves, PACs, etc, the technique may also be exploitedto detect atrial fibrillation, ventricular fibrillation or other suchdysrhythmias. In general, any of a wide variety of cardiac electricalevents or patterns occurring within the patient may be detected so longas the events can be represented by appropriate classification zones orzone sequences. Routine experimentation may be employed to identify andcharacterize such events or patterns and to generate the appropriateclassification zones or zone sequences.

What have been described are various techniques for classifying cardiacelectrical events and for adjusting or administering therapy basedthereon. In general, the embodiments described herein are merelyillustrative of the invention and should not be construed as limitingthe scope of the invention, which is to be interpreted in accordancewith the claims that follow.

1. In a device programmer for use with an implantable cardiacstimulation device implanted within a patient, a method comprising:determining vector classification zones for the patient in which thedevice is implanted, the vector classification zones representingdifferent types of electrical events within the heart of the patient;and transmitting the vector classification zones to the implantabledevice for use therein in detection of cardiac electrical events.
 2. Themethod of claim 1 wherein the step of determining the vectorclassification zones for the patient includes the steps of: inputtingsignal vectors sensed by the implanted device using a selectedcombination of electrodes, the signal vectors representative ofelectrical events within the heart of the patient; inputting ECG signalsrepresentative of the same electrical events; identifying the electricalevents based on ECG signals; and correlating the signal vectors with thecorresponding electrical events and, for each type of electrical event,calculating the characteristics of the classification zone for the eventbased on all signal vectors correlated with the event.
 3. The method ofclaim 2: wherein the vector classification zones are each represented bya direction vector and geometric range; and wherein the step ofcalculating the characteristics of the classification zone includes thestep of calculating the direction vector and the geometric range for theclassification zone based on the vectors correlated with the event. 4.The method of claim 3 wherein the step of calculating the geometricrange includes the step of adding a safety margin to the geometricrange.
 5. The method of claim 3: wherein each geometric range isrepresented by a maximum angle relative to the direction vector, aminimum vector length and a maximum vector length; and wherein the stepof calculating the geometric range includes the step of calculating themaximum angle, minimum length and maximum length for the classificationzone based on the vectors correlated with the event.
 6. The method ofclaim 5 wherein the step of calculating the direction vector includesthe step of averaging the vectors correlated with the event.
 7. Themethod of claim 6 wherein, if (a_(1,1), a_(1,2), . . . , a_(1,m)),(a_(2,1), a_(2,2), . . . , a_(2,m)), . . . , (a_(n,1), a_(n,2), . . . ,a_(n,m)) represent n signal vectors generated from m electrode pairs,then the step of averaging the signal vectors includes the step ofcalculating: $\quad\begin{matrix}{\overset{.}{\alpha} = \left( {\alpha_{1},\alpha_{2},\ldots\mspace{14mu},\alpha_{m}} \right)} \\{= \left\lbrack {\frac{\left( {a_{1,1} + a_{2,1} + \ldots + a_{n,1}} \right)}{n},\frac{\left( {a_{1,2} + a_{2,2} + \ldots + a_{n,2}} \right)}{n},\ldots\mspace{14mu},} \right.} \\{\left. \frac{\left( {a_{1,m} + a_{2,m} + \ldots + a_{n,m}} \right)}{n} \right\rbrack.}\end{matrix}$
 8. The method of claim 7 wherein the step of calculatingthe angles between each of the individual signal vectors and thedirection vector angle includes the step of calculatingθ=cos⁻¹[(a _(i)·{dot over (α)})/(∥a∥∥α{dot over (α)}∥)] wherein a_(i)represents the sensed vector and {dot over (α)} represents the directionvector.
 9. The method of claim 5 wherein the steps of calculating theminimum and maximum lengths include the steps of calculating the lengthof individual signal vectors and selecting the signal vectors having,respectively, the shortest and longest lengths.
 10. The method of claim5 wherein the step of calculating the maximum angle include the steps ofcalculating the angles between each of the individual signal vectors andthe direction vector and selecting the largest angle.
 11. The method ofclaim 5 wherein the predetermined vector classification zone isrepresented byZ _(i)={α_(i)θ_(i) , I _(i) , L _(i)} where Z_(i) is a classificationzone and {dot over (α)}_(i), θ_(i), I_(i), and L_(i) represent thedirection vector, maximum angle, minimum length, and maximum length,respectively.
 12. In a device programmer for use with an implantablecardiac stimulation device implanted within a patient, a systemcomprising: a vector-based cardiac event detection set-up unit operativeto determine vector classification zones for the patient in which thestimulation device is implanted, the vector classification zonesrepresenting different types of cardiac electrical events; and atelemetry unit operative to transmit the vector classification zones tothe implantable device.
 13. The system of claim 12 wherein the deviceprogrammer includes: a signal vector input unit operative to receivesignal vectors sensed by the implanted device using a selectedcombination of electrodes, the signal vectors representative of cardiacelectrical events within the heart of the patient; and an ECG input unitoperative to receive ECG signals representative of the same cardiacelectrical events as sensed by a surface ECG device; and wherein thevector-based cardiac event detection set-up unit is operative togenerate the vector classification zones based on the signal vectors andECG signals.
 14. The system of claim 13 wherein the vector-based cardiacevent detection set-up unit is operative to generate the vectorclassification zones by identifying the cardiac electrical events basedon the ECG signals, correlating the signal vectors with thecorresponding electrical events and, for each type of electrical event,calculating the characteristics of the classification zone for the eventbased on all signal vectors correlated with the event.
 15. In a deviceprogrammer for use with an implantable cardiac stimulation deviceadapted to be implanted within a patient and comprising a plurality ofelectrodes, a system comprising: means for inputting signal vectorssensed by the implanted device using a selected combination ofelectrodes, the signal vectors representative of cardiac electricalevents of the patient; means for inputting ECG signals representative ofthe same cardiac electrical events; means for identifying the electricalevents based on ECG signals; means for correlating the signal vectorswith the identified electrical event and, for each type of electricalevent, calculating characteristics of a classification zone for theevent based on all signal vectors correlated with the event; and meansfor transmitting the vector classification zones to the implantabledevice.